How do I install the Coreweave Common Errors skill?

Run npx skillmds add thedixitjain/coreweave-common-errors in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Coreweave Common Errors safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Coreweave Common Errors?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Coreweave Common Errors free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Coreweave Common Errors?

thedixitjain (@thedixitjain) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Coreweave Common Errors by thedixitjain

Name: Coreweave Common Errors
Rating: 4.2 (5 reviews)
Author: thedixitjain

Coreweave Common Errors

'Diagnose and fix CoreWeave GPU scheduling, pod, and networking errors. Use when pods are stuck Pending, GPUs are not allocated, or experiencing CUDA and NCCL errors. Trigger with phrases like "coreweave error", "coreweave pod pending", "coreweave gpu not found", "coreweave debug", "fix coreweave". '

thedixitjain d899908 2.3 KB Updated Sep 8, 2026 2 repo stars

File contents

CoreWeave Common Errors

Community-contributed. Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc.

Error Reference

1. Pod Stuck Pending -- No GPU Available

kubectl describe pod <pod-name> | grep -A5 Events
# "0/N nodes are available: insufficient nvidia.com/gpu"

Fix: Check GPU availability: kubectl get nodes -l gpu.nvidia.com/class=A100_PCIE_80GB. Try a different GPU type or region.

2. CUDA Out of Memory

torch.cuda.OutOfMemoryError: CUDA out of memory

Fix: Reduce batch size, enable gradient checkpointing, or use a larger GPU (A100-80GB instead of 40GB).

3. Image Pull BackOff

Fix: Create an imagePullSecret:

kubectl create secret docker-registry regcred \
  --docker-server=ghcr.io \
  --docker-username=$GH_USER \
  --docker-password=$GH_TOKEN

4. NCCL Timeout (Multi-GPU)

NCCL error: unhandled system error

Fix: Ensure all GPUs are on the same node (NVLink). For multi-node, use InfiniBand-connected nodes.

5. PVC Not Mounting

Fix: Check storage class availability: kubectl get sc. Use CoreWeave storage classes like shared-hdd-ord1 or shared-ssd-ord1.

6. Node Affinity Mismatch

Fix: List valid GPU class labels:

kubectl get nodes -o json | jq -r '.items[].metadata.labels["gpu.nvidia.com/class"]' | sort -u

7. Service Not Reachable

Fix: Check Service and Endpoints:

kubectl get svc,endpoints <service-name>

Resources

Next Steps

For diagnostics, see coreweave-debug-bundle.

Source: jeremylongshore/claude-code-plugins-plus-skills → plugins/saas-packs/coreweave-pack/skills/coreweave-common-errors/SKILL.md

---name: coreweave-common-errorsdescription: 'Diagnose and fix CoreWeave GPU scheduling, pod, and networking errors. Use when pods are stuck Pending, GPUs are not allocated, or experiencing CUDA and NCCL errors. Trigger with phrases like "coreweave error", "coreweave pod pending", "coreweave gpu not found", "coreweave debug", "fix coreweave". '---# CoreWeave Common Errors> **Community-contributed.** Not affiliated with, endorsed by, or sponsored by CoreWeave, Inc. CoreWeave is a registered trademark of CoreWeave, Inc.## Error Reference### 1. Pod Stuck Pending -- No GPU Available```textkubectl describe pod <pod-name> | grep -A5 Events# "0/N nodes are available: insufficient nvidia.com/gpu"```**Fix**: Check GPU availability: `kubectl get nodes -l gpu.nvidia.com/class=A100_PCIE_80GB`. Try a different GPU type or region.### 2. CUDA Out of Memory```torch.cuda.OutOfMemoryError: CUDA out of memory```**Fix**: Reduce batch size, enable gradient checkpointing, or use a larger GPU (A100-80GB instead of 40GB).### 3. Image Pull BackOff**Fix**: Create an imagePullSecret:```bashkubectl create secret docker-registry regcred \ --docker-server=ghcr.io \ --docker-username=$GH_USER \ --docker-password=$GH_TOKEN```### 4. NCCL Timeout (Multi-GPU)```NCCL error: unhandled system error```**Fix**: Ensure all GPUs are on the same node (NVLink). For multi-node, use InfiniBand-connected nodes.### 5. PVC Not Mounting**Fix**: Check storage class availability: `kubectl get sc`. Use CoreWeave storage classes like `shared-hdd-ord1` or `shared-ssd-ord1`.### 6. Node Affinity Mismatch**Fix**: List valid GPU class labels:```bashkubectl get nodes -o json | jq -r '.items[].metadata.labels["gpu.nvidia.com/class"]' | sort -u```### 7. Service Not Reachable**Fix**: Check Service and Endpoints:```textkubectl get svc,endpoints <service-name>```## Resources- [CoreWeave Documentation](https://docs.coreweave.com)- [GPU Instance Types](https://docs.coreweave.com/docs/platform/instances/gpu-instances)## Next StepsFor diagnostics, see `coreweave-debug-bundle`.---**Source:** [`jeremylongshore/claude-code-plugins-plus-skills`](https://github.com/jeremylongshore/claude-code-plugins-plus-skills) → `plugins/saas-packs/coreweave-pack/skills/coreweave-common-errors/SKILL.md`

Frequently asked questions